Translational Scientist, Applied Machine Learning and Agentic AI, Pharma R&D
Core
Develop agentic AI frameworks and multimodal ML models to automate prognostic and predictive model discovery in oncology, integrating clinical, genomic, and imaging data.
Role type
Senior IC applied machine learning scientist (agentic AI)
Builds
Deep agents for hypothesis generation, experimental design, and multimodal modeling
Domain
Oncology, computational biology, real-world evidence
Deliverable
production ML models
Required skills
Agentic frameworks (LangGraph), LLM application (RAG, prompt engineering), survival analysis, Python, software engineering best practices
Preferred skills
Integrative modeling of multi-modal clinical/omics data, foundation models, cloud deployment
Technologies
Python, LangGraph, LLMs, CoxPH, RSF
Responsibilities
Develop complex agentic workflows with long-horizon planning; Leverage oncology foundation models to integrate DNA, RNA, H&E, and clinical data; Collaborate with clinical scientists to define high-value use cases like clinical trial design support
Seniority
Senior, hands-on IC
